Patients were divided into hypocalcemic (HC) and normocalcemic (NC) according to the hypocalcemia definition. Data distribution normality was assessed with the Kolmogoroff–Smirnoff test. Normally or near-normally continuously distributed data were analyzed with the t-Student test and the mean and standard deviation were presented. Non-normal continuous variables were analyzed using the Mann–Whitney U test and the median and 95% confidence intervals were presented. Categorical variables were compared as proportions using the chi-square test or Fisher’s exact test. Associations between variables were studied with univariate regression, and if the p-value was <0.05, they were inserted in a multivariable logistic regression to assess their influence on the selected outcome. Independent associations were presented using odds ratios and a 95% confidence interval. Survival rates were displayed using the Kaplan–Meier curve. A p-value of <0.05 was considered to be statistically significant. All data were analyzed using StatPlus for Mac version 8 by AnalystSoft Inc., Walnut, CA, USA.
Statplus for mac version 8
Manufactured by AnalystSoft
Sourced in United States
StatPlus for Mac version 8 is a statistical analysis software for Mac operating systems. It provides a range of statistical functions and tools for data analysis and visualization.
Automatically generated - may contain errors
Lab products found in correlation
2 protocols using statplus for mac version 8
1
Statistical Analysis of Hypocalcemia Outcomes
2
Statistical Analysis of Hypocalcemia Outcomes
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Patients were divided into hypocalcemic (HC) and normocalcemic (NC) according to the hypocalcemia definition. Data distribution normality was assessed with the Kolmogoroff–Smirnoff test. Normally or near-normally continuously distributed data were analyzed with the t-Student test, and the mean and standard deviation were presented. Non-normal continuous variables were analyzed using the Mann–Whitney U test, and the median and 95% confidence intervals were presented. Categorical variables were compared as proportions using the chi-square test or Fisher’s exact test. Associations between variables were studied with univariate regression, and if the p-value was <0.05, they were inserted in a multivariable logistic regression to assess their influence on the selected outcome. Independent associations were presented using odds ratios and a 95% confidence interval. Survival rates were displayed using the Kaplan–Meier curve. A p-value of <0.05 was considered to be statistically significant. All data were analyzed using StatPlus for Mac version 8 by AnalystSoft Inc., Walnut, CA, USA.
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